COMPUTER BASED GUDIELINES TO PREVENT SUDDEN CARDIAC DEAT

指南为改善患者管理提供了系统的手段。它们的使用可以提高卫生保健的质量、适当性和有效性，并可能控制成本。然而，指南的最佳制定应包括临床医学专家、荟萃分析、决策分析、成本效益分析和证据综合的意见；在地方一级，这样的专家往往没有，或者费用高得令人望而却步。因此，国家组织经常为具有“平均”特征的人口制定指导方针。这些指南可能需要根据患者群体的特点或实践不同的地方环境进行调整。此外，传统的指导方针通常是静态的，因此随着新信息的出现可能会过时。为了解决这些问题，我们建议开发人员从决策模型中创建指导方针。这些指南包含必要的知识，允许用户根据当地患者或人群定制指南，并随着基础决策模型或证据的发展而修改指南。为了实现这一目标，我们提出的研究有三个具体目标：(1)利用基于网络的ALCHEMIST系统，开发基于循证决策模型自动创建指南的方法；(2)根据心律失常PORT（一项为期6年的多机构预防心源性猝死方法研究）的发现，创建和评估指南；(3)在随机对照试验中评估，临床医生对我们开发的基于网络的指南系统的使用和满意度与传统指南在一组假设的临床场景中提出治疗建议的比较。如果我们成功地完成了我们的具体目标，我们将拥有：(1)证明了开发人员可以使用决策模型自动创建指南；(2)使用ALCHEMIST系统根据心律失常PORT的结果创建基于证据的可定制指南，以预防心源性猝死；(3)评估了ALCHEMIST生成的指南的益处和质量；(4)为临床实施ALCHEMIST指南系统的随机试验奠定了基础。这些成就将有助于进一步AHRQ和NLM的使命，通过引导一种形式化的方法来结合证据来创建指南，并促进这些指南的传播和翻译到临床实践中。

Guidelines provide a systematic means to improve patient management. Their use can enhance the quality, appropriateness, and effectiveness of health care, and may also contain costs. Optimal development of guidelines, however, would include input from experts in clinical medicine, meta-analyses, decision analyses, cost-effectiveness analyses, and evidence synthesis; such experts often are not available, or are prohibitively costly, on a local level. Therefore, national organizations often develop guidelines for a population that has "average" characteristics. These guidelines may need to be adapted to local settings in which the characteristics of the patient population or practice are different. In addition, traditional guidelines are normally static and thus may become out of date as new information emerges. To address these problems, we propose that developers create guidelines from decision models. These guidelines contain the knowledge necessary to allow users to customize the guidelines to a local patient or population, and to modify the guidelines over time as the underlying decision model or evidence evolves. To achieve this goal, our proposed research has three specific aims: (1) to develop methods for the automated creation of guidelines from evidence-based decision models, using a web-based system called ALCHEMIST, (2) to create and evaluate guidelines based on the findings of the Cardiac Arrhythmia PORT, a 6-year multi-institutional study of methods to prevent sudden cardiac death, and (3) to evaluate, in a randomized controlled trial, clinicians' use of and their satisfaction with our developed web- based guideline system compared with traditional guidelines for making treatment recommendations on a set of hypothetical clinical scenarios. If we successfully complete our specific aims, we will have: (1) demonstrated that developers can use decision models to create guidelines automatically, (2) used the ALCHEMIST system to create an evidence-based customizable guideline for prevention of sudden cardiac death based on the findings of the Cardiac Arrhythmia PORT, (3) evaluated the benefits and quality of the ALCHEMIST- generated guidelines, and (4) laid the groundwork for a randomized trial of clinical implementation of the ALCHEMIST guideline system. These achievements will help further the missions of the AHRQ and the NLM by leading toward a formalized method for combining evidence to create guidelines, and facilitating dissemination and translation of these guidelines into clinical practice.